Junmei Ai
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer, Lipids, and Metabolism
- Cancer-related molecular mechanisms research
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- Metabolomics and Mass Spectrometry Studies
- Circular RNAs in diseases
- RNA modifications and cancer
Papers in
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- Metabolomics and Mass Spectrometry Studies 4
- Circular RNAs in diseases 2
- Extracellular vesicles in disease 1
- Sphingolipid Metabolism and Signaling 1
- Gene expression and cancer classification 1
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- MicroRNA in disease regulation 4
- Cancer-related molecular mechanisms research 4
- Co-authors
- Youping Deng (20 shared papers)Jinghe Mao (3 shared papers)Hankui Chen (6 shared papers)Ruth Welti (2 shared papers)Xinchun Zhou (2 shared papers)Shengming Dai (4 shared papers)Jeffrey R. Henegar (1 shared paper)Steven A. Bigler (1 shared paper)
- Journals
- BMC Genomics (5 papers)Oncotarget (3 papers)PLoS ONE (2 papers)BMC Systems Biology (1 paper)Journal of Clinical Oncology (1 paper)
- Partner nations
- United StatesChinaItaly
In The Last Decade
Junmei Ai
20 papers receiving 753 citations
Peers
Comparison fields: 5 of 83
- Cancer Research 330
- Molecular Biology 516
- Biochemistry 53
- Spectroscopy 102
- Horticulture 2
Countries citing papers authored by Junmei Ai
This map shows the geographic impact of Junmei Ai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Junmei Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junmei Ai more than expected).
Fields of papers citing papers by Junmei Ai
This network shows the impact of papers produced by Junmei Ai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Junmei Ai. The network helps show where Junmei Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Junmei Ai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 169 | |
| 2 | 2016 | 95 | |
| 3 | 2016 | 61 | |
| 4 | 2013 | 50 | |
| 5 | 2019 | 49 | |
| 6 | 2016 | 46 | |
| 7 | 2017 | 45 | |
| 8 | 2014 | 37 | |
| 9 | 2011 | 31 | |
| 10 | 2010 | 27 | |
| 11 | 2013 | 22 | |
| 12 | 2019 | 22 | |
| 13 | 2018 | 21 | |
| 14 | 2014 | 20 | |
| 15 | 2020 | 19 | |
| 16 | 2011 | 18 | |
| 17 | 2018 | 18 | |
| 18 | 2010 | 12 | |
| 19 | 2014 | 2 | |
| 20 | 2020 | 1 |
About Junmei Ai
Junmei Ai is a scholar working on Molecular Biology, Cancer Research, Pathology and Forensic Medicine, Oncology and Biochemistry, having authored 20 papers that have together received 765 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (4 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Cancer-related molecular mechanisms research (4 papers), Circular RNAs in diseases (2 papers), Extracellular vesicles in disease (1 paper), Sphingolipid Metabolism and Signaling (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Cancer Research (330 citations), Molecular Biology (516 citations), Biochemistry (53 citations), Spectroscopy (102 citations) and Horticulture (2 citations). Junmei Ai has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Youping Deng, Jinghe Mao, Hankui Chen, Ruth Welti, Xinchun Zhou, Shengming Dai, Jeffrey R. Henegar, Steven A. Bigler, Mary R. Roth and Charles R. Pound. Their work appears in journals such as BMC Genomics, Oncotarget, PLoS ONE, BMC Systems Biology and Journal of Clinical Oncology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.